Differential neural network identification for homogeneous dynamical systems

Mariana Ballesteros; Andrey Polyakov; Denis Efimov; Isaac Chairez; Alexander Poznyak

doi:10.1016/j.ifacol.2019.11.784

Differential neural network identification for homogeneous dynamical systems

Mariana Ballesteros, Andrey Polyakov, Denis Efimov, Isaac Chairez, Alexander Poznyak

Unidad Profesional Interdisciplinaria de Biotecnología (UPIBI)

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

In this paper, a non parametric identifier for homogeneous nonlinear systems affine in the input is proposed. The identification algorithm is based on the neural networks using sigmoidal activation functions. The learning algorithm is derived by means of Lyapunov function method and homogeneity theory. A numerical example demonstrates the performance of the proposed identifier.

Original language	English
Pages (from-to)	233-238
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	52
Issue number	16
DOIs	https://doi.org/10.1016/j.ifacol.2019.11.784
State	Published - Sep 2019
Event	11th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2019 - Vienna, Austria Duration: 4 Sep 2019 → 6 Sep 2019

Keywords

Differential neural network
Homogeneous systems
Identification
Nonlinear systems

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10.1016/j.ifacol.2019.11.784

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title = "Differential neural network identification for homogeneous dynamical systems",

abstract = "In this paper, a non parametric identifier for homogeneous nonlinear systems affine in the input is proposed. The identification algorithm is based on the neural networks using sigmoidal activation functions. The learning algorithm is derived by means of Lyapunov function method and homogeneity theory. A numerical example demonstrates the performance of the proposed identifier.",

keywords = "Differential neural network, Homogeneous systems, Identification, Nonlinear systems",

author = "Mariana Ballesteros and Andrey Polyakov and Denis Efimov and Isaac Chairez and Alexander Poznyak",

note = "Publisher Copyright: {\textcopyright} 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.; 11th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2019 ; Conference date: 04-09-2019 Through 06-09-2019",

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TY - JOUR

T1 - Differential neural network identification for homogeneous dynamical systems

AU - Ballesteros, Mariana

AU - Polyakov, Andrey

AU - Efimov, Denis

AU - Chairez, Isaac

AU - Poznyak, Alexander

PY - 2019/9

Y1 - 2019/9

N2 - In this paper, a non parametric identifier for homogeneous nonlinear systems affine in the input is proposed. The identification algorithm is based on the neural networks using sigmoidal activation functions. The learning algorithm is derived by means of Lyapunov function method and homogeneity theory. A numerical example demonstrates the performance of the proposed identifier.

AB - In this paper, a non parametric identifier for homogeneous nonlinear systems affine in the input is proposed. The identification algorithm is based on the neural networks using sigmoidal activation functions. The learning algorithm is derived by means of Lyapunov function method and homogeneity theory. A numerical example demonstrates the performance of the proposed identifier.

KW - Differential neural network

KW - Homogeneous systems

KW - Identification

KW - Nonlinear systems

UR - http://www.scopus.com/inward/record.url?scp=85077463436&partnerID=8YFLogxK

U2 - 10.1016/j.ifacol.2019.11.784

DO - 10.1016/j.ifacol.2019.11.784

M3 - Artículo de la conferencia

AN - SCOPUS:85077463436

SN - 1474-6670

VL - 52

SP - 233

EP - 238

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 16

T2 - 11th IFAC Symposium on Nonlinear Control Systems, NOLCOS 2019

Y2 - 4 September 2019 through 6 September 2019

ER -

Differential neural network identification for homogeneous dynamical systems

Abstract

Keywords

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